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当代阿耳茨海默病研究

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ISSN (Print): 1567-2050
ISSN (Online): 1875-5828

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General Research Article

日语版蒙特利尔认知评估与轻度认知障碍患者的PET影像学之间的关系

卷 16, 期 9, 2019

页: [852 - 860] 页: 9

弟呕挨: 10.2174/1567205016666190805155230

价格: $65

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摘要

背景：蒙特利尔认知评估（MoCA）测试对检测轻度认知障碍或早期痴呆症具有很高的敏感性和特异性。然而，MoCA评分与正电子发射断层扫描成像结果如何相关尚不清楚。 目的：这项前瞻性研究探讨了轻度认知障碍受试者的日语版MoCA（MoCA-J）测试与脑淀粉样蛋白沉积或脑葡萄糖代谢之间的关系。 方法：共有125位轻度认知障碍受试者接受了MoCA-J测试，并进行了淀粉样和18F-氟脱氧葡萄糖正电子发射断层扫描。进行线性相关分析和多元线性回归分析，以研究MoCA-J评分与人口统计学特征，淀粉样蛋白沉积和脑葡萄糖代谢之间的关系。此外，统计参数映射8用于MoCA-J评分和脑葡萄糖代谢的体素智能回归分析。 结果：MoCA-J得分与年龄，受教育年限以及迷你精神状态检查得分显着相关。在对年龄，性别和教育程度进行调整后，MoCA-J评分与淀粉样蛋白保留率显着负相关（β= -0.174，p = 0.031），与脑葡萄糖代谢呈正相关（β= 0.183，p = 0.044）。统计参数映射显示，日语版的MoCA评分与双侧额叶和顶叶以及左侧前突的葡萄糖代谢相关。 结论：轻度认知障碍患者的总MoCA-J得分与淀粉样蛋白沉积以及额叶和顶叶葡萄糖代谢有关。我们的发现支持MoCA-J测试对筛查阿尔茨海默氏病高风险受试者的有用性。

关键词: 轻度认知障碍，前瞻性研究，日文版的蒙特利尔认知评估，淀粉样蛋白正电子发射断层显像，18F-氟脱氧葡萄糖-正电子发射断层显像，脑区。

« Previous Next »
[1]
Petersen RC, Smith GE, Waring SC, Ivnik RJ, Tangalos EG, Kokmen E. Mild cognitive impairment: clinical characterization and outcome. Arch Neurol 56(3): 303-8. (1999).
[http://dx.doi.org/10.1001/archneur.56.3.303] [PMID: 10190820]
[2]
Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 12(3): 189-98. (1975).
[http://dx.doi.org/10.1016/0022-3956(75)90026-6] [PMID: 1202204]
[3]
Mitchell AJ. A meta-analysis of the accuracy of the mini-mental state examination in the detection of dementia and mild cognitive impairment. J Psychiatr Res 43(4): 411-31. (2009).
[http://dx.doi.org/10.1016/j.jpsychires.2008.04.014] [PMID: 18579155]
[4]
Landau SM, Harvey D, Madison CM, Koeppe RA, Reiman EM, Foster NL, et al. Associations between cognitive, functional, and FDG-PET measures of decline in AD and MCI. Neurobiol Aging 32(7): 1207-18. (2011).
[http://dx.doi.org/10.1016/j.neurobiolaging.2009.07.002] [PMID: 19660834]
[5]
Nasreddine ZS, Phillips NA, Bédirian V, Charbonneau S, Whitehead V, Collin I, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc 53(4): 695-9. (2005).
[http://dx.doi.org/10.1111/j.1532-5415.2005.53221.x] [PMID: 15817019]
[6]
Costa AS, Reich A, Fimm B, Ketteler ST, Schulz JB, Reetz K. Evidence of the sensitivity of the MoCA alternate forms in monitoring cognitive change in early Alzheimer’s disease. Dement Geriatr Cogn Disord 37(1-2): 95-103. (2014).
[http://dx.doi.org/10.1159/000351864] [PMID: 24107412]
[7]
Suzuki H, Kawai H, Hirano H, Yoshida H, Ihara K, Kim H, et al. One-Year change in the japanese version of the montreal cognitive assessment performance and related predictors in community-dwelling older adults. J Am Geriatr Soc 63(9): 1874-9. (2015).
[http://dx.doi.org/10.1111/jgs.13595] [PMID: 26313522]
[8]
Pasi M, Salvadori E, Poggesi A, Ciolli L, Del Bene A, Marini S, et al. White matter microstructural damage in small vessel disease is associated with Montreal cognitive assessment but not with mini mental state examination performances: vascular mild cognitive impairment Tuscany study. Stroke 46(1): 262-4. (2015).
[http://dx.doi.org/10.1161/STROKEAHA.114.007553] [PMID: 25395414]
[9]
Akanuma K, Meguro K, Kato Y, Takahashi Y, Nakamura K, Yamaguchi S. Impaired attention function based on the Montréal Cognitive Assessment in vascular dementia patients with frontal hypoperfusion: the Osaki-Tajiri project. J Clin Neurosci 28: 128-32. (2016).
[http://dx.doi.org/10.1016/j.jocn.2015.08.047] [PMID: 26778514]
[10]
Bloudek LM, Spackman DE, Blankenburg M, Sullivan SD. Review and meta-analysis of biomarkers and diagnostic imaging in Alzheimer’s disease. J Alzheimers Dis 26(4): 627-45. (2011).
[http://dx.doi.org/10.3233/JAD-2011-110458] [PMID: 21694448]
[11]
Ma Y, Zhang S, Li J. Predictive accuracy of amyloid imaging for progression from mild cognitive impairment to Alzheimer disease with different lengths of follow-up: a meta-analysis.[Corrected] Medicine (Baltimore) 93(27)e150 (2014).
[http://dx.doi.org/10.1097/MD.0000000000000150] [PMID: 25501055]
[12]
Jack CR Jr, Knopman DS, Jagust WJ, Petersen RC, Weiner MW, Aisen PS, et al. Tracking pathophysiological processes in Alzheimer’s disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol 12(2): 207-16. (2013).
[http://dx.doi.org/10.1016/S1474-4422(12)70291-0] [PMID: 23332364]
[13]
Del Brutto OH, Mera RM, Zambrano M, Soriano F, Lama J. Global cortical atrophy (GCA) associates with worse performance in the Montreal Cognitive Assessment (MoCA). A population-based study in community-dwelling elders living in rural Ecuador. Arch Gerontol Geriatr 60(1): 206-9. (2015).
[http://dx.doi.org/10.1016/j.archger.2014.09.010] [PMID: 25306507]
[14]
Ritter A, Hawley N, Banks SJ, Miller JB. The association between Montreal Cognitive Assessment memory scores and hippocampal volume in a neurodegenerative disease sample. J Alzheimers Dis 58(3): 695-9. (2017).
[http://dx.doi.org/10.3233/JAD-161241] [PMID: 28453481]
[15]
Topiwala A, Allan CL, Valkanova V. Zsoldos E1, Filippini N1, Sexton CE, et al. Resilience and MRI correlates of cognitive impairment in community-dwelling elders. Br J Psychiatry 207(5): 435-9. (2015).
[http://dx.doi.org/10.1192/bjp.bp.114.152363] [PMID: 26338988]
[16]
Maeshima E, Okumura Y, Tatsumi J, Tomokane S, Ikeshima A. Cognitive function in middle-aged and older adults participating in synchronized swimming-exercise. J Phys Ther Sci 29(1): 148-51. (2017).
[http://dx.doi.org/10.1589/jpts.29.148] [PMID: 28210062]
[17]
Nara M, Sugie M, Takahashi T, Koyama T, Sengoku R, Fujiwara Y, et al. Japanese version of the Montreal Cognitive Assessment cut-off score to clarify improvement of mild cognitive impairment after exercise training in community-dwelling older adults. Geriatr Gerontol Int 18(6): 833-8. (2018).
[http://dx.doi.org/10.1111/ggi.13253] [PMID: 29392877]
[18]
Abe Y, Kimura N, Takahashi R, Gotou M, Mizukami K, Uchida H, et al. Relationship between cytokine levels in the cerebrospinal fluid and 11C-Pittsburgh compound B retention in patients with mild cognitive impairment. Geriatr Gerontol Int 17(11): 1907-13. (2017).
[http://dx.doi.org/10.1111/ggi.12991] [PMID: 28261965]
[19]
Takemaru M, Kimura N, Abe Y, Goto M, Matsubara E. The evaluation of brain perfusion SPECT using an easy Z-score imaging system in the mild cognitive impairment subjects with brain amyloid-β deposition. Clin Neurol Neurosurg 160: 111-5. (2017).
[http://dx.doi.org/10.1016/j.clineuro.2017.06.018] [PMID: 28715708]
[20]
Herholz K, Salmon E, Perani D, Baron JC, Holthoff V, Frölich L, et al. Discrimination between Alzheimer dementia and controls by automated analysis of multicenter FDG PET. Neuroimage 17(1): 302-16. (2002).
[http://dx.doi.org/10.1006/nimg.2002.1208] [PMID: 12482085]
[21]
Jack CR Jr, Lowe VJ, Senjem ML, Weigand SD, Kemp BJ, Shiung MM, et al. 11C PiB and structural MRI provide complementary information in imaging of Alzheimer’s disease and amnestic mild cognitive impairment. Brain 131(Pt 3): 665-80. (2008).
[http://dx.doi.org/10.1093/brain/awm336] [PMID: 18263627]
[22]
Paul R, Lane EM, Tate DF, Heaps J, Romo DM, Akbudak E, et al. Neuroimaging signatures and cognitive correlates of the montreal cognitive assessment screen in a nonclinical elderly sample. Arch Clin Neuropsychol 26(5): 454-60. (2011).
[http://dx.doi.org/10.1093/arclin/acr017] [PMID: 21642663]
[23]
Jung Y, Whitwell JL, Duffy JR, Strand EA, Machulda MM, Senjem ML, et al. Amyloid burden correlates with cognitive decline in Alzheimer’s disease presenting with aphasia. Eur J Neurol 21(7): 1040-3. (2014).
[http://dx.doi.org/10.1111/ene.12331] [PMID: 24330306]
[24]
Jagust WJ, Landau SM, Shaw LM. Alzheimer’s Disease Neuroimaging Initiative. Relationships between biomarkers in aging and dementia. Neurology 73(15): 1193-9. (2009).
[http://dx.doi.org/10.1212/WNL.0b013e3181bc010c] [PMID: 19822868]
[25]
Johnson KA, Schultz A, Betensky RA, Becker JA, Sepulcre J, Rentz D, et al. Tau positron emission tomographic imaging in aging and early Alzheimer disease. Ann Neurol 79(1): 110-9. (2016).
[http://dx.doi.org/10.1002/ana.24546] [PMID: 26505746]
[26]
Jansen WJ, Ossenkoppele R, Tijms BM. Fagan AM6, Hansson O7, Klunk WE, et al. Amyloid biomarker study group. association of cerebral amyloid-β aggregation with cognitive functioning in persons without dementia. JAMA Psychiatry 75(1): 84-95. (2018).
[http://dx.doi.org/10.1001/jamapsychiatry.2017.3391] [PMID: 29188296]
[27]
Landau SM, Horng A, Fero A, Jagust WJ. Alzheimer’s Disease Neuroimaging Initiative. Amyloid negativity in patients with clinically diagnosed Alzheimer disease and MCI. Neurology 86(15): 1377-85. (2016).
[http://dx.doi.org/10.1212/WNL.0000000000002576] [PMID: 26968515]
[28]
Nakaoku Y, Oishi N, Hase Y, Saito S, Mitsueda T, Matsui M, et al. Montreal Cognitive Assessment score correlates with regional cerebral blood flow in post-stroke patients. Clin Neurol Neurosurg 174: 68-74. (2018).
[http://dx.doi.org/10.1016/j.clineuro.2018.09.004] [PMID: 30216810]
[29]
Shivamurthy VK, Tahari AK, Marcus C, Subramaniam RM. Brain FDG PET and the diagnosis of dementia. AJR Am J Roentgenol 204(1)W76-85 (2015).
[http://dx.doi.org/10.2214/AJR.13.12363] [PMID: 25539279]
[30]
Pakrasi S, O’Brien JT. Emission tomography in dementia. Nucl Med Commun 26(3): 189-96. (2005).
[http://dx.doi.org/10.1097/00006231-200503000-00003] [PMID: 15722899]
[31]
Nagata K, Maruya H, Yuya H, Terashi H, Mito Y, Kato H, et al. Can PET data differentiate Alzheimer’s disease from vascular dementia? Ann N Y Acad Sci 903: 252-61. (2000).
[http://dx.doi.org/10.1111/j.1749-6632.2000.tb06375.x] [PMID: 10818514]
[32]
Ma HR, Sheng LQ, Pan PL, Wang GD, Luo R, Shi HC, et al. Cerebral glucose metabolic prediction from amnestic mild cognitive impairment to Alzheimer’s dementia: a meta-analysis. Transl Neurodegener 7(7): 9. (2018).
[http://dx.doi.org/10.1186/s40035-018-0114-z] [PMID: 29713467]
[33]
Drzezga A, Lautenschlager N, Siebner H, Riemenschneider M, Willoch F, Minoshima S, et al. Cerebral metabolic changes accompanying conversion of mild cognitive impairment into Alzheimer’s disease: a PET follow-up study. Eur J Nucl Med Mol Imaging 30(8): 1104-13. (2003).
[http://dx.doi.org/10.1007/s00259-003-1194-1] [PMID: 12764551]
[34]
Foldi NS, Lobosco JJ, Schaefer LA. The effect of attentional dysfunction in Alzheimer’s disease: theoretical and practical implications. Semin Speech Lang 23(2): 139-50. (2002).
[http://dx.doi.org/10.1055/s-2002-24990] [PMID: 11951174]
[35]
Guedj E, Barbeau EJ, Didic M, Felician O, de Laforte C, Ranjeva JP, et al. Effects of medial temporal lobe degeneration on brain perfusion in amnestic MCI of AD type: deafferentation and functional compensation? Eur J Nucl Med Mol Imaging 36(7): 1101-12. (2009).
[http://dx.doi.org/10.1007/s00259-009-1060-x] [PMID: 19224210]
[36]
Ushijima Y, Okuyama C, Mori S, Nakamura T, Kubota T, Nishimura T. Relationship between cognitive function and regional cerebral blood flow in Alzheimer’s disease. Nucl Med Commun 23(8): 779-84. (2002).
[http://dx.doi.org/10.1097/00006231-200208000-00012] [PMID: 12124484]
[37]
Desgranges B, Baron JC, de la Sayette V, Petit-Taboué MC, Benali K, Landeau B, et al. The neural substrates of memory systems impairment in Alzheimer’s disease. A PET study of resting brain glucose utilization. Brain 121(Pt 4): 611-31. (1998).
[http://dx.doi.org/10.1093/brain/121.4.611] [PMID: 9577389]
[38]
Leech R, Sharp DJ. The role of the posterior cingulate cortex in cognition and disease. Brain 137(Pt 1): 12-32. (2014).
[http://dx.doi.org/10.1093/brain/awt162] [PMID: 23869106]
[39]
Besson JA, Crawford JR, Parker DM, Ebmeier KP, Best PV, Gemmell HG, et al. Multimodal imaging in Alzheimer’s disease. The relationship between MRI, SPECT, cognitive and pathological changes. Br J Psychiatry 157: 216-20. (1990).
[http://dx.doi.org/10.1192/bjp.157.2.216] [PMID: 2224371]
[40]
Nobili F, Brugnolo A, Calvini P, Copello F, De Leo C, Girtler N, et al. Resting SPECT-neuropsychology correlation in very mild Alzheimer’s disease. Clin Neurophysiol 116(2): 364-75. (2005).
[http://dx.doi.org/10.1016/j.clinph.2004.09.001] [PMID: 15661114]
[41]
O’Brien JT, Eagger S, Syed GM, Sahakian BJ, Levy R. A study of regional cerebral blood flow and cognitive performance in Alzheimer’s disease. J Neurol Neurosurg Psychiatry 55(12): 1182-7. (1992).
[http://dx.doi.org/10.1136/jnnp.55.12.1182] [PMID: 1479398]
[42]
Hyman BT, Van Hoesen GW, Damasio AR. Memory-related neural systems in Alzheimer’s disease: an anatomic study. Neurology 40(11): 1721-30. (1990).
[http://dx.doi.org/10.1212/WNL.40.11.1721] [PMID: 2234428]
[43]
Mosconi L, Tsui WH, De Santi S, Li J, Rusinek H, Convit A, et al. Reduced hippocampal metabolism in MCI and AD: automated FDG-PET image analysis. Neurology 64(11): 1860-7. (2005).
[http://dx.doi.org/10.1212/01.WNL.0000163856.13524.08] [PMID: 15955934]
[44]
Ouchi Y, Nobezawa S, Okada H, Yoshikawa E, Futatsubashi M, Kaneko M. Altered glucose metabolism in the hippocampal head in memory impairment. Neurology 51(1): 136-42. (1998).
[http://dx.doi.org/10.1212/WNL.51.1.136] [PMID: 9674792]
[45]
Ishii K, Sasaki M, Yamaji S, Sakamoto S, Kitagaki H, Mori E. Paradoxical hippocampus perfusion in mild-to-moderate Alzheimer’s disease. J Nucl Med 39(2): 293-8. (1998).
[PMID: 9476938]
[46]
Ishii K, Sasaki H, Kono AK, Miyamoto N, Fukuda T, Mori E. Comparison of gray matter and metabolic reduction in mild Alzheimer’s disease using FDG-PET and voxel-based morphometric MR studies. Eur J Nucl Med Mol Imaging 32(8): 959-63. (2005).
[http://dx.doi.org/10.1007/s00259-004-1740-5] [PMID: 15800784]
[47]
Ishii K, Sasaki M, Yamaji S, Sakamoto S, Kitagaki H, Mori E. Relatively preserved hippocampal glucose metabolism in mild Alzheimer’s disease. Dement Geriatr Cogn Disord 9(6): 317-22. (1998).
[http://dx.doi.org/10.1159/000017083] [PMID: 9769444]

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